ADDRESS - active demand for the smart grids of the future

Belhomme, R.; Asua, Ramon Cerero Real De; Valtorta, Giovanni; Paice, Andrew; Bouffard, François; Rooth, Rudy; Losi, Arturo

doi:10.1049/ic:20080438

Cited by 51 publications

(29 citation statements)

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“…This can be done either by 1) dictating the power consumption of each device but basing control decisions on feedback from loads' end-use function status, or 2) by directly controlling the end-use function (e.g., temperature setpoint) with the expectation that power consumption will change according to some known model. As with the services described in the previous section, there are challenges associated with coordinating thousands or even millions of loads in a way that minimizes end-use impact, or guarantees a certain level of end-use function [45], [46]. These challenges stem from, among other things, information and communications bandwidth requirements, model fidelity, and controller design.…”

Section: A Dual Objectives Of Load Controlmentioning

confidence: 99%

Achieving Controllability of Electric Loads

2011

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This paper discusses actively involving highly distributed loads in power system control actions; an overview of system control objectives is provided.By Duncan S. Callaway, Member IEEE, and Ian A. Hiskens, Fellow IEEE ABSTRACT | This paper discusses conceptual frameworks for actively involving highly distributed loads in power system control actions. The context for load control is established by providing an overview of system control objectives, including economic dispatch, automatic generation control, and spinning reserve. The paper then reviews existing initiatives that seek to develop load control programs for the provision of power system services. We then discuss some of the challenges to achieving a load control scheme that balances device-level objectives with power system-level objectives. One of the central premises of the paper is that, in order to achieve full responsiveness, direct load control (as opposed to price response) is required to enable fast time scale, predictable control opportunities, especially for the provision of ancillary services such as regulation and contingency reserves. Centralized, hierarchical, and distributed control architectures are discussed along with benefits and disadvantages, especially in relation to integration with the legacy power system control architecture. Implications for the supporting communications infrastructure are also considered. Fully responsive load control is illustrated in the context of thermostatically controlled loads and plug-in electric vehicles.

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Section: A Dual Objectives Of Load Controlmentioning

confidence: 99%

Achieving Controllability of Electric Loads

2011

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“…The project coordinator is ENEL Distribuzione SpA and the consortium consists of 25 partners from 11 European countries spanning the entire electricity supply chain, qualified R&D bodies, SMEs and manufacturers [2]. As already mentioned, the aim of the project is to develop a comprehensive commercial and technical framework for the development of Active Demand in the smart grids of the future.…”

Section: Target Objectives and Methodologymentioning

confidence: 99%

“…In ADDRESS, only domestic and small commercial consumers are considered, and both the loads and possible embedded generation at their premises will be taken into account. More specifically [2]: -ADDRESS will develop technical solutions both at the consumers' premises and at the power system level to enable AD and to allow real-time response to requests from markets and/or from other power system participants. -This implies identifying the possible barriers against AD deployment and proposing solutions to remove these barriers.…”

Section: Target Objectives and Methodologymentioning

confidence: 99%

ADDRESS: scenarios and architecture for active demand development in the smart grids of the future

Peeters

Belhomme

Batlle

et al. 2009

IET Conference Publications

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“…Existing distribution networks present an inflexible structure which makes them inadequate to allow a large spread of Distributed Energy Resources (DERs), such as distributed generators from renewable energy sources, cogeneration facilities, energy storage systems (including electric vehicles), and controllable loads (i.e., adopting active demand) [1][2][3]. To overcome this problem, the smart grid paradigm is asserted and promoted by extensive use of Information and Communication Technologies [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources

et al. 2016

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A key issue in Low Voltage (LV) distribution systems is to identify strategies for the optimal management and control in the presence of Distributed Energy Resources (DERs). To reduce the number of variables to be monitored and controlled, virtual levels of aggregation, called Virtual Microgrids (VMs), are introduced and identified by using new models of the distribution system. To this aim, this paper, revisiting and improving the approach outlined in a conference paper, presents a sensitivity-based model of an LV distribution system, supplied by an Medium/Low Voltage (MV/LV) substation and composed by several feeders, which is suitable for the optimal management and control of the grid and for VM definition. The main features of the proposed method are: it evaluates the sensitivity coefficients in a closed form; it provides an overview of the sensitivity of the network to the variations of each DER connected to the grid; and it presents a limited computational burden. A comparison of the proposed method with both the exact load flow solutions and a perturb-and-observe method is discussed in a case study. Finally, the method is used to evaluate the impact of the DERs on the nodal voltages of the network.

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ADDRESS - active demand for the smart grids of the future

Cited by 51 publications

References 1 publication

Achieving Controllability of Electric Loads

Achieving Controllability of Electric Loads

ADDRESS: scenarios and architecture for active demand development in the smart grids of the future

Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources

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